A Decentralized Reputation Management Model for Enhanced IoV Networks With 5G Broadcast Services

This paper investigates the challenges of data trust sharing faced by Internet of Vehicles (IoV) network with 5G broadcast services. Particularly we develop a decentralized IoV reputation management model with spatiotemporal feature perception fusion (RMM-STFP) based on blockchain. The proposed reputation evaluation method evaluates the reputation value of nodes from the two aspects of time continuity and spatial transitivity and thus improves the identification accuracy of malicious nodes. To further accelerate the dissemination of reputation data, we have constructed a blockchain-based management storage system, where PBFT consensus scheme combines reputation and Bayesian inference. Finally, numerical results are given to justify the superiority of our proposed scheme. When proportion of malicious nodes reaches 45%, the accuracy of our proposed method is 94.5%, and the suppression rate of malicious messages is 83%. Moreover, compared with the traditional PBFT consensus scheme, the consensus delay and communication overhead are reduced by 87.57% and 78.45%, respectively, and the transaction throughput is increased by 70.65%.

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Publication Details

Journal
IEEE Transactions on Broadcasting
Published
2024-08-05
DOI
https://doi.org/10.1109/tbc.2024.3434745
Citations
6
Primary Topic
Advanced Data and IoT Technologies
Type
article
Field-Weighted Citation Impact
1.25

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article

A Decentralized Reputation Management Model for Enhanced IoV Networks With 5G Broadcast Services

Yueming Lu, Ziping Wang, Jinxin Zuo, Hao Wu et al.
6 citations
IEEE Transactions on Broadcasting
Advanced Data and IoT Technologies
1.25
article

A Decentralized Reputation Management Model for Enhanced IoV Networks With 5G Broadcast Services

Yueming Lu, Ziping Wang, Jinxin Zuo, Hao Wu, Peng Yu, Weixuan Xie, Chenqing Guo
article en
6 citations

Abstract

This paper investigates the challenges of data trust sharing faced by Internet of Vehicles (IoV) network with 5G broadcast services. Particularly we develop a decentralized IoV reputation management model with spatiotemporal feature perception fusion (RMM-STFP) based on blockchain. The proposed reputation evaluation method evaluates the reputation value of nodes from the two aspects of time continuity and spatial transitivity and thus improves the identification accuracy of malicious nodes. To further accelerate the dissemination of reputation data, we have constructed a blockchain-based management storage system, where PBFT consensus scheme combines reputation and Bayesian inference. Finally, numerical results are given to justify the superiority of our proposed scheme. When proportion of malicious nodes reaches 45%, the accuracy of our proposed method is 94.5%, and the suppression rate of malicious messages is 83%. Moreover, compared with the traditional PBFT consensus scheme, the consensus delay and communication overhead are reduced by 87.57% and 78.45%, respectively, and the transaction throughput is increased by 70.65%.

IEEE Transactions on BroadcastingVol. 71(1)
Beijing University of Posts and Telecommunications (CN), National Computer Network Emergency Response Technical Team/Coordination Center of Chinar (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 20%
Advanced Data and IoT Technologies
1.25
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A Decentralized Reputation Management Model for Enhanced IoV Networks With 5G Broadcast Services — Yueming Lu, Ziping Wang, et al. · IEEE Transactions on Broadcasting (2024) | TGRS Research Map | TGRS